code: def conv3x3(
      in_planes: int,
      out_planes: int,
      stride: int = 1,
      groups: int = 1,
      dilation: int = 1,
  ) -> nn.Conv2d:
      """3x3 convolution with padding."""
      return nn.Conv2d(
          in_planes,
          out_planes,
          kernel_size=3,
          stride=stride,
          padding=dilation,
          groups=groups,
          bias=False,
          dilation=dilation,
      )
  
imports: from typing import Callable, Dict, List, Optional, Type
  import torch
  from torch import nn
  from kornia.core import Module, Tensor, concatenate, stack
  from kornia.utils.helpers import map_location_to_cpu
label_desc: Use image node_id 2 for calling a global function with example usage: conv3x3(in_planes, out_planes, stride, groups, dilation) and returns: nn